{"id":"https://openalex.org/W4387803484","doi":"https://doi.org/10.1109/igarss52108.2023.10283265","title":"Dense Ship Detection Guided by Centrality Prior Information in SAR Images","display_name":"Dense Ship Detection Guided by Centrality Prior Information in SAR Images","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387803484","doi":"https://doi.org/10.1109/igarss52108.2023.10283265"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10283265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss52108.2023.10283265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114804039","display_name":"Yu Zhang","orcid":"https://orcid.org/0000-0002-9331-8629"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Zhang","raw_affiliation_strings":["Tsinghua University,Department of Electronic Engineering,Beijing,China","Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Electronic Engineering,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100737123","display_name":"Xueqian Wang","orcid":"https://orcid.org/0000-0002-8632-6073"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueqian Wang","raw_affiliation_strings":["Tsinghua University,Department of Electronic Engineering,Beijing,China","Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Electronic Engineering,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100438655","display_name":"Gang Li","orcid":"https://orcid.org/0000-0001-9755-2781"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Li","raw_affiliation_strings":["Tsinghua University,Department of Electronic Engineering,Beijing,China","Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Electronic Engineering,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114804039"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.4407,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.75895658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"5265","last_page":"5268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.8083445429801941},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7679256200790405},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6862840056419373},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.683614194393158},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6423097848892212},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.6217250823974609},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.616493284702301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5925588607788086},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.533659040927887},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5166833400726318},{"id":"https://openalex.org/keywords/centrality","display_name":"Centrality","score":0.48946845531463623},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4394884407520294},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3609451651573181},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3517186939716339},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16731521487236023},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11944690346717834},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07823944091796875},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0690559446811676}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.8083445429801941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7679256200790405},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6862840056419373},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.683614194393158},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6423097848892212},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6217250823974609},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.616493284702301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5925588607788086},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.533659040927887},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5166833400726318},{"id":"https://openalex.org/C53811970","wikidata":"https://www.wikidata.org/wiki/Q5062194","display_name":"Centrality","level":2,"score":0.48946845531463623},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4394884407520294},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3609451651573181},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3517186939716339},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16731521487236023},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11944690346717834},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07823944091796875},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0690559446811676},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10283265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss52108.2023.10283265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1585937684","https://openalex.org/W2163405822","https://openalex.org/W2565639579","https://openalex.org/W2774244034","https://openalex.org/W2904480641","https://openalex.org/W2963857746","https://openalex.org/W3011032387","https://openalex.org/W3018757597","https://openalex.org/W3033996275","https://openalex.org/W3129289673","https://openalex.org/W4294186599","https://openalex.org/W6760424586","https://openalex.org/W6777046832"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"The":[0],"detection":[1,55,127],"of":[2,9,16,33,49,90,109,133],"densely":[3],"distributed":[4],"ship":[5,66],"targets":[6],"is":[7,73],"one":[8],"the":[10,14,30,34,47,77,82,87,91,93,100,104,114,125,130,138],"hot":[11],"issues":[12],"in":[13,53,86],"context":[15],"convolutional":[17],"neural":[18],"network":[19,101],"(CNN)-based":[20],"synthetic":[21],"aperture":[22],"radar":[23],"(SAR)":[24],"image":[25],"processing.":[26],"In":[27],"this":[28,59],"case,":[29],"bounding":[31],"boxes":[32],"ships":[35,119],"may":[36],"overlap":[37,83],"with":[38,117,137],"each":[39],"other.":[40],"Traditional":[41],"detectors":[42],"do":[43],"not":[44],"specifically":[45],"consider":[46,76],"processing":[48],"overlapping":[50],"areas,":[51],"resulting":[52],"low":[54],"performance.":[56],"To":[57],"address":[58],"problem,":[60],"we":[61],"proposed":[62],"a":[63],"new":[64],"SAR":[65],"detector,":[67],"where":[68],"classification":[69],"confidence":[70],"score-based":[71],"method":[72,123],"developed":[74],"to":[75,98,102,107],"centrality":[78],"prior":[79],"information":[80],"among":[81],"areas.":[84],"Then,":[85],"shallow":[88],"layers":[89],"network,":[92],"auxiliary":[94],"heads":[95],"are":[96],"used":[97],"guide":[99],"learn":[103],"features":[105],"related":[106],"centers":[108],"ships.":[110],"Experimental":[111],"results":[112],"on":[113],"open":[115],"datasets":[116],"dense":[118],"show":[120],"that":[121],"our":[122],"achieves":[124],"better":[126],"performance":[128],"without":[129],"obvious":[131],"increase":[132],"computation":[134],"burden":[135],"compared":[136],"current":[139],"state-of-the-art":[140],"detectors.":[141]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}